Overview

Dataset statistics

Number of variables5
Number of observations450
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.6 KiB
Average record size in memory42.3 B

Variable types

Categorical2
Numeric1
Boolean1
DateTime1

Dataset

Description연도,접수번호,소속구,당첨여부,당첨시간
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15720/S/1/datasetView.do

Alerts

연도 has constant value ""Constant
당첨여부 has constant value ""Constant
접수번호 has unique valuesUnique
당첨시간 has unique valuesUnique

Reproduction

Analysis started2024-05-11 00:40:57.066067
Analysis finished2024-05-11 00:40:58.111498
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
2019
450 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 450
100.0%

Length

2024-05-11T00:40:58.368474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:40:58.749835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 450
100.0%

접수번호
Real number (ℝ)

UNIQUE 

Distinct450
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean545.08667
Minimum3
Maximum1127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2024-05-11T00:40:59.239904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile54.8
Q1257
median518.5
Q3809.25
95-th percentile1082.2
Maximum1127
Range1124
Interquartile range (IQR)552.25

Descriptive statistics

Standard deviation332.53757
Coefficient of variation (CV)0.61006367
Kurtosis-1.2079844
Mean545.08667
Median Absolute Deviation (MAD)279
Skewness0.12824477
Sum245289
Variance110581.24
MonotonicityNot monotonic
2024-05-11T00:40:59.879075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
709 1
 
0.2%
938 1
 
0.2%
32 1
 
0.2%
301 1
 
0.2%
356 1
 
0.2%
986 1
 
0.2%
647 1
 
0.2%
15 1
 
0.2%
293 1
 
0.2%
1038 1
 
0.2%
Other values (440) 440
97.8%
ValueCountFrequency (%)
3 1
0.2%
5 1
0.2%
10 1
0.2%
13 1
0.2%
15 1
0.2%
16 1
0.2%
24 1
0.2%
26 1
0.2%
27 1
0.2%
28 1
0.2%
ValueCountFrequency (%)
1127 1
0.2%
1125 1
0.2%
1124 1
0.2%
1121 1
0.2%
1117 1
0.2%
1115 1
0.2%
1114 1
0.2%
1112 1
0.2%
1109 1
0.2%
1108 1
0.2%

소속구
Categorical

Distinct25
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
종로구
 
20
영등포구
 
20
강서구
 
20
도봉구
 
20
마포구
 
20
Other values (20)
350 

Length

Max length4
Median length3
Mean length3.08
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강동구
2nd row강동구
3rd row강동구
4th row강동구
5th row송파구

Common Values

ValueCountFrequency (%)
종로구 20
 
4.4%
영등포구 20
 
4.4%
강서구 20
 
4.4%
도봉구 20
 
4.4%
마포구 20
 
4.4%
송파구 20
 
4.4%
성동구 20
 
4.4%
강남구 19
 
4.2%
서초구 19
 
4.2%
관악구 19
 
4.2%
Other values (15) 253
56.2%

Length

2024-05-11T00:41:00.456568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로구 20
 
4.4%
강서구 20
 
4.4%
도봉구 20
 
4.4%
마포구 20
 
4.4%
송파구 20
 
4.4%
성동구 20
 
4.4%
영등포구 20
 
4.4%
강남구 19
 
4.2%
서초구 19
 
4.2%
관악구 19
 
4.2%
Other values (15) 253
56.2%

당첨여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size582.0 B
True
450 
ValueCountFrequency (%)
True 450
100.0%
2024-05-11T00:41:00.942254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

당첨시간
Date

UNIQUE 

Distinct450
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
Minimum2019-02-20 10:40:33.003000
Maximum2019-02-20 10:44:15.413000
2024-05-11T00:41:01.534558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:41:01.996946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-05-11T00:40:57.319698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T00:41:02.389931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수번호소속구
접수번호1.0000.361
소속구0.3611.000
2024-05-11T00:41:02.711178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
접수번호소속구
접수번호1.0000.132
소속구0.1321.000

Missing values

2024-05-11T00:40:57.681318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T00:40:58.001971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연도접수번호소속구당첨여부당첨시간
02019709강동구Y2019-02-20 10:44:15.413
12019416강동구Y2019-02-20 10:44:15.393
220191109강동구Y2019-02-20 10:44:15.296
32019368강동구Y2019-02-20 10:44:15.274
42019922송파구Y2019-02-20 10:44:15.193
52019381송파구Y2019-02-20 10:44:15.175
62019661송파구Y2019-02-20 10:44:15.042
72019721송파구Y2019-02-20 10:44:15.024
82019436강남구Y2019-02-20 10:44:14.933
92019776강남구Y2019-02-20 10:44:14.915
연도접수번호소속구당첨여부당첨시간
4402019843동작구Y2019-02-20 10:40:33.072
4412019621구로구Y2019-02-20 10:40:33.064
4422019686중랑구Y2019-02-20 10:40:33.056
4432019677도봉구Y2019-02-20 10:40:33.049
444201981중랑구Y2019-02-20 10:40:33.041
4452019261영등포구Y2019-02-20 10:40:33.033
44620191084영등포구Y2019-02-20 10:40:33.026
4472019320강남구Y2019-02-20 10:40:33.019
4482019176동작구Y2019-02-20 10:40:33.011
449201979도봉구Y2019-02-20 10:40:33.003